bims-midomi Biomed News
on MDM2 and mitochondria
Issue of 2026–10–11
two papers selected by
Gavin McStay, Liverpool John Moores University
  1. KT-253, a highly potent and selective MDM2 protein degrader, eliminates malignant myelofibrosis stem/progenitor cells.
  2. Nanopore sensing with machine learning-assisted analysis for real-time single-molecule detection of MDM2-p53TAD interactions.
  1. Leukemia. 2026 Oct 06.
    KT-253, a highly potent and selective MDM2 protein degrader, eliminates malignant myelofibrosis stem/progenitor cells.
    Min Lu, Lijuan Xia, Yogesh Chutake, Joyoti Dey, Ronald Hoffman.
      Approximately 96% of myelofibrosis (MF) patients express wild-type (WT) p53. MF hematopoietic stem/progenitor cells (HSPCs) overexpress MDM2 that degrades WTp53, thereby supporting MF HSPC survival. Although MDM2 small-molecule inhibitors (SMIs) are clinically effective, their benefit is compromised by an inability to sufficiently deplete MF HSPCs. KT-253 degrades MDM2 and overcomes the p53-dependent feedback loop that restores MDM2 levels observed with the use of MDM2 SMIs such as AMG-232. We evaluated the effects of KT-253 using MPN cell lines, primary MF CD34+ cells, and a mouse xenograft model. KT-253 activity was correlated with activation of the p53 pathway and upregulation of p53 downstream genes, including p21, NOXA, and PUMA in WTp53 UKE-1 cells but not p53 mutant cells. KT-253 treatment induced apoptosis of primary MF CD34+ cells at a tenfold lower concentration than AMG-232 and prevented the upregulation of MDM2 seen with AMG-232. Low doses of KT-253 reduced total MF colony and JAK2V617F+ colony numbers to a far greater extent than log-higher doses of AMG-232 (60% and 71% versus 20% and 10%, respectively). Mouse xenograft studies indicated that KT-253 more effectively depleted JAK2V617F+ MF marrow-repopulating cells. These findings support the further clinical evaluation of MDM2 degraders for the treatment of MF patients.
    DOI:  https://doi.org/10.1038/s41375-026-03163-2
  2. Biosens Bioelectron. 2026 Oct 03. pii: S0956-5663(26)00928-0. [Epub ahead of print]315 119295
    Nanopore sensing with machine learning-assisted analysis for real-time single-molecule detection of MDM2-p53TAD interactions.
    Jinhyung Kim, Taeyoung Ha, Soyoung Park, Dongwoo Kang, Sunju Lee, Seongwon Lee, Sohee Oh, Minji Chung, Seung-Wook Chi, Seung Jun Kim, YunKyong Hyon, Mi-Kyung Lee.
      Protein-protein interactions (PPIs) play pivotal roles in physiological processes but remain challenging drug targets. Conventional PPI detection methods often suffer from limited sensitivity and require time- and labor-intensive procedures, such as fluorophore labeling, restricting their utility in drug discovery. Here, we present a YaxAB nanopore sensing platform coupled with machine learning-assisted signal analysis for label-free, real-time, single-molecule detection of PPIs between the oncogenic murine double minute 2 (MDM2) protein and p53TAD1. Proteins were efficiently captured into the YaxAB nanopore, and free MDM2 generated ionic current signatures readily distinguishable from those of the MDM2-p53TAD1 complex. To enable rapid and quantitative event analysis, we developed a machine learning-based classification framework that accurately distinguished free MDM2, MDM2-p53TAD1 complexes, and MDM2-drug complexes directly from nanopore current traces. This integrated platform enabled automated interpretation of single-molecule events, real-time monitoring of PPI inhibition by small-molecule MDM2 antagonists, and estimation of drug binding affinity without labeling or ensemble averaging. Taken together, the YaxAB nanopore sensing and machine learning analysis platform provides a versatile approach for single-molecule interaction analysis, with potential applications in drug discovery, diagnostics, including protein probe-biomarker interaction assays.
    DOI:  https://doi.org/10.1016/j.bios.2026.119295
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